PTENES
TRACK 3

🥊 Critique & Decision

Attack your own ideas before others do — then decide with explicit criteria, not with intuition disguised as analysis. These are families 04 (Critique and Red Team) and 05 (Comparison and Decision).

By the end of the track, you’ll run a complete personal red team and turn difficult choices into matrices, rankings, and bets with exit conditions.

2
Modules
16
Topics
~2h30
Duration
Intermediate
Level
0%
0 of 16
Your thesis or proposal survived the red team? yes no /rank /decide /robust Decision with declared criterion

The track’s rule: an idea without a red team review doesn’t make it to the decision table.

Course roadmap

Detailed content

3.1~75 min

🥊 Red team and robustness

The 10 commands in family 04 — adversarial challenge, failure simulation, and strengthening under uncertainty.

What it is:

The protocol requires you to refute or challenge the premise before agreeing—disagreement comes first, support comes later (if it holds up).

Why learn:

Models are complacent by default; /pushback turns agreement into something that must be earned.

Key concepts:

refutation first · agreement earned · antidote to flattery.

What it is:

Attacks the central thesis with the strongest possible objections and asks for an explicit defense of each.

Why learn:

A thesis that has never been challenged is a hypothesis with borrowed confidence.

Key concepts:

strong objection · explicit defense · tested thesis.

What it is:

Simulates a capable adversary trying to bring down a plan, system, or argument by exploiting real vulnerabilities.

Why learn:

It’s cheaper to find the failure in the simulator than in the market.

Key concepts:

attack vector · vulnerability · mitigation.

What it is:

Put the plan through extreme conditions (/stress) and map failure modes with detection and mitigation (/failure).

Why learn:

Every plan has a load limit; it’s better to learn it in a test than on a bad Tuesday.

Key concepts:

extreme condition · failure mode · detection trigger.

What it is:

Assumes the project has ALREADY failed and works backward: what were the likely causes?

Why learn:

Thinking of the future as the past frees the team to say the unthinkable — risks become legitimate.

Key concepts:

prior retrospective · plausible cause · early mitigation.

What it is:

Actively look for the case that overturns the general rule — the exception that refutes or limits it.

Why learn:

One well-documented exception is worth more than a hundred confirming examples.

Key concepts:

negative case · rule delimitation · honest scope.

What it is:

Identify cognitive biases in the reasoning (/bias) and areas the analysis hasn’t even considered (/blindspots).

Why learn:

Confirmation bias and survivorship bias silently distort even technically impeccable analyses.

Key concepts:

confirmation bias · survivorship bias · unexamined area.

What it is:

Redesigns the solution to work reasonably well across several scenarios—not perfectly in just one.

Why learn:

Robustness trades a fragile optimum for something good that can withstand the real world.

Key concepts:

multi-scenario performance · hedge · margin of safety.

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3.2~75 min

🎯 Comparison and decision

The 10 commands in family 05 — criteria, weights, rankings, matrices, and bets with a stopping point.

What it is:

Set measurable criteria and their weights BEFORE evaluating the options.

Why learn:

The criterion chosen after the favorite option is selected magically adjusts so that option wins.

Key concepts:

a priori criterion · relative weight · fixed yardstick.

What it is:

Sorts options by criteria and explains each ranking — a ranking without justification is just numbered preference.

Why learn:

It’s the most commonly used decision command in day-to-day work; with parameters, it becomes a team standard.

Key concepts:

ordering · positional rationale · criteria=impact,cost,risk.

What it is:

Assigns scores by criterion on a defined scale, showing how the total score is composed.

Why learn:

A composite score reveals whether the win came from one dominant criterion or broad consistency.

Key concepts:

anchor scale · score per criterion · transparent weighting.

What it is:

Produces a side-by-side comparison by dimension — without forcing a premature verdict.

Why learn:

Separating comparison from decision keeps a first impression from closing the window for analysis.

Key concepts:

comparable dimension · suspension of judgment.

What it is:

Close the process: one recommendation with evidence, degree of reversibility, and cost of changing your mind.

Why learn:

Reversible decisions call for speed; irreversible ones call for depth. Knowing which is which changes everything.

Key concepts:

two-way door · cost of reversal · clear commitment.

What it is:

Build the full matrix: evaluate each alternative against every criterion, applying the weights.

Why learn:

The matrix exposes trade-offs hidden behind polished narratives.

Key concepts:

weighted matrix · justified cell · sensitivity.

What it is:

Eliminates dominated options and presents the frontier where no criterion can improve without worsening another.

Why learn:

Half the "options" on any list shouldn't be there—ruling them out saves entire meetings.

Key concepts:

dominated option · Pareto frontier · efficiency.

What it is:

/bet structures the bet: upside, downside, size, and triggers; /stop defines the objective condition for ending it without drama.

Why learn:

A bet without a stop-loss becomes a zombie project — kept alive by pride and costing a lot every month.

Key concepts:

return asymmetry · kill criteria · graceful exit.

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